This paper presents a robust method to correct for intensity differences across a series of aligned stained histological slices. The method is made up of two steps. First, for each slice, a scale-space analysis of the histogram provides a set of alternative interpretations in terms of tissue classes. Each of these interpretations can lead to a different classification of the related slice. A simple heuristics selects for each slice the most plausible interpretation. Then, an iterative procedure refines the interpretation selections across the series in order to maximize a score measuring the spatial consistency of the classifications across contiguous slices. Results are presented for a series of 121 baboon slices. © Springer-Verlag Berlin Heidelberg 2004.
CITATION STYLE
Dauguet, J., Mangin, J. F., Delzescaux, T., & Frouin, V. (2004). Robust inter-slice intensity normalization using histogram scale-space analysis. In Lecture Notes in Computer Science (Vol. 3216, pp. 242–249). Springer Verlag. https://doi.org/10.1007/978-3-540-30135-6_30
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